Exploring Data: Distributions
a) Data and Variables.
b) Displaying and Describing Distributions.
c) Measures of Center.
d) Measures of Spread
a1) What are the types of data?
a2) What makes data catagorical?
a3) What makes data quantitative?
b1) What is the shape of a distribution and how is it determined?
b2) How are unusual features of a distribution determined?
c1) What are measures of center and how are they calculated?
d1) What are measures of spread and how are they calculated?
a1) Determine if data is quantitative or catagorical.
b1) Graphing distributions of univariate data ( stemplots, histograms, boxplots)
b2) Determining the shape of a graph (uniform, skewed left, skewed right, mound-shaped, symmetric, gaps, clusters).
b3) Determining any unusual features of a distribution (outliers).
c1) Calculating measures of center (mean, median, mode).
d1) Calculating measures of spread (range, interquartile range, standard deviation).
d2) Calculating posititon (quartiles, percentiles, standardized scores (z-scores)).
7 question free response test
Unit 2
Exploring Data: Comparisons and Relationships
a) Comparing Distributions: Quantitative Variables.
b) Comparing Distributions: Catagorical Variables.
c) Graphical Displays of Asssociation.
d) Correlation Coefficient
e) Least Squares Regression.
a1) How are distributions of quantitative variables compared?
b1) How can categorical data be expressed with frequency tables and bar charts?
b2) What are marginal and joint frequencies of two-way tables?
b3) What are conditional and relative frequencies for catagorical data?
b4) What is independence and how is it determined?
c1) What is association?
c2) How is bivariate data analyzed?
c3) How are patterns in bivariate data found?
d1) What is correlation and how is it measured?
d2) What is linearity and how is it measured?
e1) What are lines of best fit?
e2) How are lines of best fit calculated?
e3) What are residuals, outliers and influential points?
e4) What is a residual plot used for?
e5) Why should non-linear bivariate data be transformed?
e6) How should non-linear bivariate data be transformed?
a1) Compare centers, spreads and shapes of quantitative variables.
b1) Express categorical data with tables, charts, graphs, and distributions.
b2) Determine if random variables are independent.
c1) How to graph a scatterplot.
d1) How to find and interpret the correlation coefficient.
e1) How to find the least-squares regression line.
e2) How to graph a residual plot.
e3) How to determine outliers and influential points.
e4) How to linearize bivariate data using a logarithmic transformation.
e5) How to linearize bivariate data using a power transformation.
4 question free response test
Unit 3
Collecting Data
a) Sampling
b) Designing Studies
a1) What is a census and how is a census conducted?
a2) What is a sample survey?
a3) What are the characteristics of a well-designed and well-conducted survey?
a4) What is a population?
a5) What is a sample?
a6) What is random selection?
a7) What are sources of bias in sampling and surveys?
a8) What are the basic sampling methods?
b1) What are the characteristics of a well-designed and well-conducted experiment?
b2) What are treatments, control groups, experimental units, random assignment and replication?
b3) What are sources of bias and confounding in experiments?
b4) What are blind and double-blind experiments?
b5) What is a placebo and what is the placebo effect?
b5) What is a completely randomized design of an experiment?
b6) What is blocking?
b7) What is a randomized block design of an experiment?
a1) Taking a census.
a2) Taking a survey.
a3) Conducting a simple random sample.
a4) Conducting a stratified random sample.
a5) Conducting a cluster sample.
b1) Plan an experiment.
b2) Conduct an experiment.
b3) Analyze experimental results.
17 question Multiple Choice and 1 free response test.
Unit 4
Randomness in Data
a) Probability.
b) Normal Distributions.
c) Sampling Distributions: Proportions.
d) Sampling Distributions: Means.
e) Central Limit Theorem.
a1) How is probability interpreted?
a2) How is long-run relative frequecy related to probability?
a3) When is the addition and multiplication rules of probability used?
a4) How is conditional probability calculated?
a5) What is independence and how is it determined?
a6) How can you simulate random behavior and probability distributions?
b1) How can the normal distribution be used as a model for measurement?
b2) What are the properties of the normal distribution?
b3) How are tables used in the calculation of normal probabilities?
b4) How is technology used in the calculation of normal probabilities?
c1) What are the properties of a sampling distibution of a sample proportion?
c2) How are probabilities calculated using a sampling distribution of sample proportions?
d1) What are the properties of a sampling distibution of a sample means?
d2) How are probabilities calculated using a sampling distribution of sample means?
e1) What is the Central Limit Theorem and how is it used?
a1) Calculate and interpret simple probabilities.
a2) Calculate and interpret conditional probabilities.
a3) Determine if random variables are independent.
b1) Calculate, graph and interpret a normal probability plot.
b2) Calculate and interpret normal probabilities.
c1) Calculate and interpret sampling distribution probabilities for sample proportions.
d1) Calculate and interpret sampling distribution probabilities for sample means.
e1) Use the Central Limit Theorem.
16 question Multiple Choice and 2 question free response test.
Unit 5
Inference from Data: Principles
a) Confidence Intervals: Proportions.
b) Confidence Intervals: Means.
c) Tests of Significance: Proportions.
d) Tests of Significance: Means.
e) More Inference Considerations.
a1) How are population parameters and margins of error estimated?
a2) What are the properties of point estimators?
a3) What is the logic of confidence intervals?
a4) What is the meaning of a confidence interval?
a5) What is the meaning of a confidence level?
a6) What are the properties of confidence intervals?
a7) What is a large sample confidence interval for proportions used for?
a8) How is a large sample confidence interval calculated for a proportion?
a9) How is a large sample confidence interval for proportions interpreted?
b1) What is a confidence interval for means used for?
b2) How is a confidence interval for means calculated?
b3) How is a confidence interval for means interpreted?
b4) What is matched pair design?
b5) What is a confidence interval for matched pairs used for?
b6) How is a confidence interval for matched pairs calculated?
b7) How is a confidence interval for matched pairs interpreted?
c1) What is the logic of significance testing?
c2) What are the null and alternative hypotheses?
c3) What is the difference between a one-sided and two-sided significance test?
c4) What is a large sample significance test for proportions used for?
c5) How is a large sample significance test carried out for a proportion?
c6) How is a large sample significance test for proportions interpreted?
d1) What is a signficance test for means used for?
d2) How is a signficance test for means carried out?
d3) How is a signficance test for means interpreted?
d4) What is a significance test for matched pairs used for?
d5) How is a significance test for matched pairs carried out?
d6) How is a significance test for matched pairs interpreted?
e1) What are type I and type II errors?
e2) What is the power of a significance test?
a1) Calculate and interpret confidence intervals for proportions.
b1) Calculate and interpret confidence intervals for means.
c1) Calculate and interpret significance tests for proportions.
d1) Calculate and interpret significance tests for means.
e1) Interpret Type I and Type II errors.
e2) Interpret the power of a significance test.
14 question Multiple Choice and 2 question free response test.
Unit 6
Inference from Data: Comparisons and Relationships.
a) Comparing Two Proportions.
b) Comparing Two Means.
c) Inference for Two-Way Tables.
d) Inference for Correlation and Regression.
1) What are the properties of sampling distribution of a difference between two independent sample proportions?
a2) What is a large sample confidence interval for a difference of two proportions used for?
a3) How is a large sample confidence interval calculated for a difference of two proportions?
a4) How is a large sample confidence interval for a difference of two proportions interpreted?
a5) What is a large sample significance test for a difference of two proportions used for?
a6) How is a large sample significance test carried out for a difference of two proportions?
a7) How is a large sample significance test for a difference of two proportions interpreted?
b1) What are the properties of sampling distibution of a difference between two independent sample means?
b2) What is a confidence interval for a difference of two means (paired and unpaired)used for?
b3) How is a confidence interval calculated for a difference of two means (paired and unpaired)?
b4) How is a confidence interval for a difference of two means (paired and unpaired) interpreted?
b5) What is a significance test for a difference of two means (paired and unpaired) used for?
b6) How is a significance test calculated for a difference of two means (paired and unpaired)?
b7) How is asignificance test for a difference of two means (paired and unpaired) interpreted?
c1) What are the properties of Chi-Square distribution?
c2) What is a Chi-Square test for goodness of fit used for?
c3) How is a Chi-Square test for goodness of fit calculated?
c4) How is a Chi-Square test for goodness of fit interpreted?
c5) What is a Chi-Square test for homogeneity of proportions used for?
c6) How is a Chi-Square test for homogeneity of proportions calculated?
c7) How is a Chi-Square test for homogeneity of proportions interpreted?
c8) What is a Chi-Square test for independence used for?
c9) How is a Chi-Square test for independence calculated?
c10) How is a Chi-Square test for independence interpreted?
d1) What is a confidence interval for the slope of a least-squares regression line used for?
d2) How is a confidence interval for the slope of a least-squares regression line calculated?
d3) How is a confidence interval for the slope of a least-squares regression line interpreted?
d4) What is a significance test for the slope of a least-squares regression line used for?
d5) How is a significance test for the slope of a least-squares regression line calculated?
d6) How is a significance test for the slope of a least-squares regression line interpreted?
a1) Calculate and interpret confidence intervals for a difference of two proportions.
a2) Calculate and interpret significance tests for a difference of two proportions.
b1) Calculate and interpret confidence intervals for a difference of two means (paired and unpaired).
b2) Calculate and interpret significance tests for a difference of two means (paired and unpaired).
c1) How to calculate and interpret a Chi-Square test for goodness of fit.
c2) How to calculate and interpret a Chi-Square test for homogeneity of proportions.
c3) How to calculate and interpret a Chi-Square test for independence.
d1) How to calculate and interpret a confidence interval for the slope of a least-squares regression line.
d2) How to calculate and interpret a significance test for the slope of a least-squares regression line.
a) Data and Variables.
b) Displaying and Describing Distributions.
c) Measures of Center.
d) Measures of Spread
a2) What makes data catagorical?
a3) What makes data quantitative?
b1) What is the shape of a distribution and how is it determined?
b2) How are unusual features of a distribution determined?
c1) What are measures of center and how are they calculated?
d1) What are measures of spread and how are they calculated?
b1) Graphing distributions of univariate data ( stemplots, histograms, boxplots)
b2) Determining the shape of a graph (uniform, skewed left, skewed right, mound-shaped, symmetric, gaps, clusters).
b3) Determining any unusual features of a distribution (outliers).
c1) Calculating measures of center (mean, median, mode).
d1) Calculating measures of spread (range, interquartile range, standard deviation).
d2) Calculating posititon (quartiles, percentiles, standardized scores (z-scores)).
a) Comparing Distributions: Quantitative Variables.
b) Comparing Distributions: Catagorical Variables.
c) Graphical Displays of Asssociation.
d) Correlation Coefficient
e) Least Squares Regression.
b1) How can categorical data be expressed with frequency tables and bar charts?
b2) What are marginal and joint frequencies of two-way tables?
b3) What are conditional and relative frequencies for catagorical data?
b4) What is independence and how is it determined?
c1) What is association?
c2) How is bivariate data analyzed?
c3) How are patterns in bivariate data found?
d1) What is correlation and how is it measured?
d2) What is linearity and how is it measured?
e1) What are lines of best fit?
e2) How are lines of best fit calculated?
e3) What are residuals, outliers and influential points?
e4) What is a residual plot used for?
e5) Why should non-linear bivariate data be transformed?
e6) How should non-linear bivariate data be transformed?
b1) Express categorical data with tables, charts, graphs, and distributions.
b2) Determine if random variables are independent.
c1) How to graph a scatterplot.
d1) How to find and interpret the correlation coefficient.
e1) How to find the least-squares regression line.
e2) How to graph a residual plot.
e3) How to determine outliers and influential points.
e4) How to linearize bivariate data using a logarithmic transformation.
e5) How to linearize bivariate data using a power transformation.
a) Sampling
b) Designing Studies
a2) What is a sample survey?
a3) What are the characteristics of a well-designed and well-conducted survey?
a4) What is a population?
a5) What is a sample?
a6) What is random selection?
a7) What are sources of bias in sampling and surveys?
a8) What are the basic sampling methods?
b1) What are the characteristics of a well-designed and well-conducted experiment?
b2) What are treatments, control groups, experimental units, random assignment and replication?
b3) What are sources of bias and confounding in experiments?
b4) What are blind and double-blind experiments?
b5) What is a placebo and what is the placebo effect?
b5) What is a completely randomized design of an experiment?
b6) What is blocking?
b7) What is a randomized block design of an experiment?
a2) Taking a survey.
a3) Conducting a simple random sample.
a4) Conducting a stratified random sample.
a5) Conducting a cluster sample.
b1) Plan an experiment.
b2) Conduct an experiment.
b3) Analyze experimental results.
a) Probability.
b) Normal Distributions.
c) Sampling Distributions: Proportions.
d) Sampling Distributions: Means.
e) Central Limit Theorem.
a2) How is long-run relative frequecy related to probability?
a3) When is the addition and multiplication rules of probability used?
a4) How is conditional probability calculated?
a5) What is independence and how is it determined?
a6) How can you simulate random behavior and probability distributions?
b1) How can the normal distribution be used as a model for measurement?
b2) What are the properties of the normal distribution?
b3) How are tables used in the calculation of normal probabilities?
b4) How is technology used in the calculation of normal probabilities?
c1) What are the properties of a sampling distibution of a sample proportion?
c2) How are probabilities calculated using a sampling distribution of sample proportions?
d1) What are the properties of a sampling distibution of a sample means?
d2) How are probabilities calculated using a sampling distribution of sample means?
e1) What is the Central Limit Theorem and how is it used?
a2) Calculate and interpret conditional probabilities.
a3) Determine if random variables are independent.
b1) Calculate, graph and interpret a normal probability plot.
b2) Calculate and interpret normal probabilities.
c1) Calculate and interpret sampling distribution probabilities for sample proportions.
d1) Calculate and interpret sampling distribution probabilities for sample means.
e1) Use the Central Limit Theorem.
a) Confidence Intervals: Proportions.
b) Confidence Intervals: Means.
c) Tests of Significance: Proportions.
d) Tests of Significance: Means.
e) More Inference Considerations.
a2) What are the properties of point estimators?
a3) What is the logic of confidence intervals?
a4) What is the meaning of a confidence interval?
a5) What is the meaning of a confidence level?
a6) What are the properties of confidence intervals?
a7) What is a large sample confidence interval for proportions used for?
a8) How is a large sample confidence interval calculated for a proportion?
a9) How is a large sample confidence interval for proportions interpreted?
b1) What is a confidence interval for means used for?
b2) How is a confidence interval for means calculated?
b3) How is a confidence interval for means interpreted?
b4) What is matched pair design?
b5) What is a confidence interval for matched pairs used for?
b6) How is a confidence interval for matched pairs calculated?
b7) How is a confidence interval for matched pairs interpreted?
c1) What is the logic of significance testing?
c2) What are the null and alternative hypotheses?
c3) What is the difference between a one-sided and two-sided significance test?
c4) What is a large sample significance test for proportions used for?
c5) How is a large sample significance test carried out for a proportion?
c6) How is a large sample significance test for proportions interpreted?
d1) What is a signficance test for means used for?
d2) How is a signficance test for means carried out?
d3) How is a signficance test for means interpreted?
d4) What is a significance test for matched pairs used for?
d5) How is a significance test for matched pairs carried out?
d6) How is a significance test for matched pairs interpreted?
e1) What are type I and type II errors?
e2) What is the power of a significance test?
b1) Calculate and interpret confidence intervals for means.
c1) Calculate and interpret significance tests for proportions.
d1) Calculate and interpret significance tests for means.
e1) Interpret Type I and Type II errors.
e2) Interpret the power of a significance test.
a) Comparing Two Proportions.
b) Comparing Two Means.
c) Inference for Two-Way Tables.
d) Inference for Correlation and Regression.
a2) What is a large sample confidence interval for a difference of two proportions used for?
a3) How is a large sample confidence interval calculated for a difference of two proportions?
a4) How is a large sample confidence interval for a difference of two proportions interpreted?
a5) What is a large sample significance test for a difference of two proportions used for?
a6) How is a large sample significance test carried out for a difference of two proportions?
a7) How is a large sample significance test for a difference of two proportions interpreted?
b1) What are the properties of sampling distibution of a difference between two independent sample means?
b2) What is a confidence interval for a difference of two means (paired and unpaired)used for?
b3) How is a confidence interval calculated for a difference of two means (paired and unpaired)?
b4) How is a confidence interval for a difference of two means (paired and unpaired) interpreted?
b5) What is a significance test for a difference of two means (paired and unpaired) used for?
b6) How is a significance test calculated for a difference of two means (paired and unpaired)?
b7) How is asignificance test for a difference of two means (paired and unpaired) interpreted?
c1) What are the properties of Chi-Square distribution?
c2) What is a Chi-Square test for goodness of fit used for?
c3) How is a Chi-Square test for goodness of fit calculated?
c4) How is a Chi-Square test for goodness of fit interpreted?
c5) What is a Chi-Square test for homogeneity of proportions used for?
c6) How is a Chi-Square test for homogeneity of proportions calculated?
c7) How is a Chi-Square test for homogeneity of proportions interpreted?
c8) What is a Chi-Square test for independence used for?
c9) How is a Chi-Square test for independence calculated?
c10) How is a Chi-Square test for independence interpreted?
d1) What is a confidence interval for the slope of a least-squares regression line used for?
d2) How is a confidence interval for the slope of a least-squares regression line calculated?
d3) How is a confidence interval for the slope of a least-squares regression line interpreted?
d4) What is a significance test for the slope of a least-squares regression line used for?
d5) How is a significance test for the slope of a least-squares regression line calculated?
d6) How is a significance test for the slope of a least-squares regression line interpreted?
a2) Calculate and interpret significance tests for a difference of two proportions.
b1) Calculate and interpret confidence intervals for a difference of two means (paired and unpaired).
b2) Calculate and interpret significance tests for a difference of two means (paired and unpaired).
c1) How to calculate and interpret a Chi-Square test for goodness of fit.
c2) How to calculate and interpret a Chi-Square test for homogeneity of proportions.
c3) How to calculate and interpret a Chi-Square test for independence.
d1) How to calculate and interpret a confidence interval for the slope of a least-squares regression line.
d2) How to calculate and interpret a significance test for the slope of a least-squares regression line.